Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "72" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 46 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 44 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459861 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 2.890450 | -0.004186 | 0.057098 | -0.130105 | -0.069698 | 1.786504 | 4.335575 | -0.450969 | 0.7162 | 0.7026 | 0.3860 | nan | nan |
| 2459860 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 2.768844 | -0.218449 | -0.670461 | -0.713387 | 1.089483 | 0.439137 | 1.780107 | -0.715737 | 0.7237 | 0.7012 | 0.3834 | nan | nan |
| 2459859 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 227.650273 | 227.763890 | inf | inf | 3835.950909 | 3836.016351 | 7646.941507 | 7651.640825 | nan | nan | nan | nan | nan |
| 2459858 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 2.659017 | 0.137409 | 0.077333 | -0.216021 | 1.823888 | 2.977129 | 7.342142 | -0.335564 | 0.7366 | 0.7082 | 0.3907 | 3.323830 | 2.610527 |
| 2459857 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 18.422024 | 21.943842 | 6.090364 | 7.823125 | 117.598407 | 183.524976 | 56.935800 | 53.254250 | 0.7089 | 0.7008 | 0.4090 | nan | nan |
| 2459856 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.43% | 34.86% | 3.546647 | -0.415391 | -0.739495 | -0.693615 | 0.659850 | 0.636337 | 2.874079 | -0.592173 | 0.7295 | 0.7205 | 0.3771 | 2.045410 | 1.572927 |
| 2459855 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 5.025679 | 0.099769 | -0.932121 | -0.762083 | -0.224503 | 0.447990 | 2.050980 | -0.868444 | 0.7119 | 0.7354 | 0.4059 | 3.137446 | 2.743305 |
| 2459854 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 5.216047 | 0.282806 | -0.562569 | 0.270186 | 0.591667 | 0.197961 | 3.815808 | -0.254326 | 0.7280 | 0.7551 | 0.4127 | 3.387023 | 2.758928 |
| 2459853 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 30.90% | 3.158922 | -0.164275 | -0.499045 | 0.805604 | 0.782115 | 0.998524 | 3.192798 | -0.706583 | 0.7528 | 0.7111 | 0.4002 | 1.901057 | 1.582480 |
| 2459852 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 4.687721 | -1.282230 | -0.569835 | 1.561132 | 0.275550 | 1.113965 | 0.112315 | 1.098416 | 0.8485 | 0.8553 | 0.2184 | 5.037918 | 4.496439 |
| 2459851 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 11.76% | 72.73% | 3.467735 | -0.148706 | -0.294940 | 1.219992 | 1.257718 | -0.389554 | 0.678110 | -0.197179 | 0.7696 | 0.7654 | 0.3188 | 4.923886 | 3.590139 |
| 2459850 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 4.934380 | 0.005180 | -0.369330 | 0.660503 | 1.300181 | 0.462962 | 2.632888 | -0.493894 | 0.7552 | 0.7749 | 0.3272 | 3.385252 | 2.580750 |
| 2459849 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 5.120988 | -0.047779 | 0.231616 | 2.276854 | 0.729421 | 0.847685 | 4.224641 | -0.919807 | 0.7538 | 0.7673 | 0.3345 | 3.954871 | 3.264341 |
| 2459848 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 5.455758 | 0.315058 | -0.332744 | 1.953983 | 2.868572 | 0.512514 | 1.355371 | -0.698851 | 0.7307 | 0.7684 | 0.3562 | 3.432040 | 2.903607 |
| 2459847 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 5.385550 | 0.242377 | -0.482259 | 2.359695 | 1.600871 | 0.254344 | 1.446241 | -0.772847 | 0.7319 | 0.7074 | 0.4096 | 3.538916 | 2.939863 |
| 2459846 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 6.740728 | -0.843480 | 0.231330 | 2.513828 | 0.256139 | 0.733640 | 1.749586 | -0.703331 | 0.8553 | 0.7081 | 0.4436 | 3.560158 | 2.900062 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 6.511194 | 0.305396 | 0.541800 | 3.469741 | 1.598021 | 0.992584 | 10.237398 | -0.467183 | 0.7402 | 0.7640 | 0.3601 | 16.251941 | 36.304866 |
| 2459844 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 38.424467 | 51.275607 | 93.156976 | 110.863856 | 262.041704 | 225.625252 | 58.750752 | 54.561811 | 0.8825 | 0.6300 | 0.5734 | nan | nan |
| 2459843 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 8.565153 | 0.180660 | -0.673490 | 0.372974 | 70.876600 | 81.654332 | 12.431728 | 0.329012 | 0.7550 | 0.7691 | 0.3752 | 4.580657 | 3.636482 |
| 2459838 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 68.180054 | 63.039408 | 67.469852 | 71.626450 | 68.516764 | 104.042383 | 634.576751 | 752.140789 | 0.0184 | 0.0168 | 0.0011 | 0.813894 | 0.805595 |
| 2459833 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 15.907395 | 19.204526 | 28.828414 | 32.516680 | 313.831405 | 287.818811 | 43.249272 | 30.952028 | 0.7341 | 0.4585 | 0.5089 | nan | nan |
| 2459832 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 5.257168 | -0.680048 | -0.821762 | 0.973286 | 0.145441 | 0.925396 | 2.774753 | -0.971438 | 0.0970 | 0.0830 | 0.0151 | 1.206210 | 1.208930 |
| 2459831 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -0.856848 | -0.405035 | -0.488023 | 3.982738 | 0.937315 | -0.329987 | 1.696374 | 1.203954 | 0.0323 | 0.0371 | 0.0009 | nan | nan |
| 2459830 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 5.505755 | -1.049080 | -0.789439 | 1.407915 | 3.183383 | -0.825843 | 4.539166 | -1.207966 | 0.0957 | 0.0686 | 0.0140 | 1.226195 | 1.223577 |
| 2459829 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.729247 | -0.271854 | -0.631210 | 0.825063 | 1.512398 | 0.555522 | 7.736295 | -0.995937 | 0.0792 | 0.0709 | 0.0111 | 6.216159 | 10.771415 |
| 2459828 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.606530 | -0.616560 | -0.618729 | 0.504790 | 3.976918 | -0.594447 | 4.823386 | -1.053786 | 0.1014 | 0.0771 | 0.0158 | 1.246435 | 1.248741 |
| 2459827 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 5.653505 | -0.401279 | -0.421397 | 1.954498 | 1.284032 | 0.441090 | 6.968338 | 3.673110 | 0.0847 | 0.0779 | 0.0130 | 1.237231 | 1.232689 |
| 2459826 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.869640 | -0.951539 | -0.332650 | 2.025250 | 4.323041 | -0.567175 | 5.332582 | -1.111612 | 0.0886 | 0.0785 | 0.0172 | 0.951513 | 0.953645 |
| 2459825 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.807696 | -0.694903 | -0.751555 | 1.066199 | 1.311611 | -0.923016 | 4.163518 | -0.246065 | 0.1061 | 0.0896 | 0.0195 | 1.207357 | 1.193451 |
| 2459824 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.986092 | -0.055399 | -0.678177 | 1.496756 | 0.955029 | -0.152017 | 1.222230 | -0.837659 | 0.0796 | 0.0744 | 0.0122 | 1.170652 | 1.165635 |
| 2459823 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 1.125065 | -0.657474 | -0.697792 | 1.883983 | -0.343370 | 1.756559 | 1.868401 | -1.509048 | 0.0890 | 0.0743 | 0.0119 | 1.125285 | 1.125856 |
| 2459822 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 3.573627 | -0.841520 | -0.621610 | 1.482194 | 1.386167 | -0.341102 | 6.634668 | 4.188646 | 0.1147 | 0.1016 | 0.0202 | 1.154528 | 1.151649 |
| 2459821 | digital_ok | 0.00% | 11.29% | 11.29% | 0.00% | 13.16% | 60.53% | 3.190428 | -0.620855 | -0.697152 | 1.597476 | 1.412981 | -0.410916 | 2.708131 | -0.004376 | 0.7323 | 0.6064 | 0.4233 | 3.592948 | 3.023811 |
| 2459820 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 4.328342 | -0.456575 | -0.622889 | 1.455982 | 3.501769 | 1.003664 | 5.900627 | -0.718279 | 0.7821 | 0.7120 | 0.3928 | 4.101593 | 3.813323 |
| 2459817 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 55.26% | 2.216198 | -1.436970 | -0.461257 | 0.952967 | 0.364642 | 0.523069 | -0.094568 | -0.836959 | 0.8301 | 0.7097 | 0.4805 | 2.453931 | 2.115073 |
| 2459816 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 76.74% | 3.548312 | -0.959766 | -0.845555 | 1.809948 | 0.976436 | 1.360679 | 0.905524 | -1.138694 | 0.8494 | 0.6293 | 0.5586 | 3.821007 | 3.293824 |
| 2459815 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 57.89% | 2.455962 | -0.823916 | -0.847435 | 1.503651 | 1.016628 | 1.342223 | 3.891432 | -1.152500 | 0.8253 | 0.7134 | 0.4956 | 3.180371 | 2.697083 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 7.584946 | -0.744531 | -0.698578 | 1.114648 | 2.707307 | 0.316794 | 4.853688 | -0.262671 | 0.8026 | 0.7381 | 0.3980 | 15.656179 | 12.038925 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 4.335575 | -0.004186 | 2.890450 | -0.130105 | 0.057098 | 1.786504 | -0.069698 | -0.450969 | 4.335575 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 2.768844 | 2.768844 | -0.218449 | -0.670461 | -0.713387 | 1.089483 | 0.439137 | 1.780107 | -0.715737 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Power | inf | 227.650273 | 227.763890 | inf | inf | 3835.950909 | 3836.016351 | 7646.941507 | 7651.640825 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 7.342142 | 0.137409 | 2.659017 | -0.216021 | 0.077333 | 2.977129 | 1.823888 | -0.335564 | 7.342142 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | nn Temporal Variability | 183.524976 | 21.943842 | 18.422024 | 7.823125 | 6.090364 | 183.524976 | 117.598407 | 53.254250 | 56.935800 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 3.546647 | 3.546647 | -0.415391 | -0.739495 | -0.693615 | 0.659850 | 0.636337 | 2.874079 | -0.592173 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 5.025679 | 0.099769 | 5.025679 | -0.762083 | -0.932121 | 0.447990 | -0.224503 | -0.868444 | 2.050980 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 5.216047 | 0.282806 | 5.216047 | 0.270186 | -0.562569 | 0.197961 | 0.591667 | -0.254326 | 3.815808 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 3.192798 | -0.164275 | 3.158922 | 0.805604 | -0.499045 | 0.998524 | 0.782115 | -0.706583 | 3.192798 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 4.687721 | 4.687721 | -1.282230 | -0.569835 | 1.561132 | 0.275550 | 1.113965 | 0.112315 | 1.098416 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 3.467735 | 3.467735 | -0.148706 | -0.294940 | 1.219992 | 1.257718 | -0.389554 | 0.678110 | -0.197179 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 4.934380 | 4.934380 | 0.005180 | -0.369330 | 0.660503 | 1.300181 | 0.462962 | 2.632888 | -0.493894 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 5.120988 | 5.120988 | -0.047779 | 0.231616 | 2.276854 | 0.729421 | 0.847685 | 4.224641 | -0.919807 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 5.455758 | 0.315058 | 5.455758 | 1.953983 | -0.332744 | 0.512514 | 2.868572 | -0.698851 | 1.355371 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 5.385550 | 0.242377 | 5.385550 | 2.359695 | -0.482259 | 0.254344 | 1.600871 | -0.772847 | 1.446241 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 6.740728 | 6.740728 | -0.843480 | 0.231330 | 2.513828 | 0.256139 | 0.733640 | 1.749586 | -0.703331 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 10.237398 | 0.305396 | 6.511194 | 3.469741 | 0.541800 | 0.992584 | 1.598021 | -0.467183 | 10.237398 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Variability | 262.041704 | 38.424467 | 51.275607 | 93.156976 | 110.863856 | 262.041704 | 225.625252 | 58.750752 | 54.561811 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | nn Temporal Variability | 81.654332 | 0.180660 | 8.565153 | 0.372974 | -0.673490 | 81.654332 | 70.876600 | 0.329012 | 12.431728 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | nn Temporal Discontinuties | 752.140789 | 63.039408 | 68.180054 | 71.626450 | 67.469852 | 104.042383 | 68.516764 | 752.140789 | 634.576751 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Variability | 313.831405 | 19.204526 | 15.907395 | 32.516680 | 28.828414 | 287.818811 | 313.831405 | 30.952028 | 43.249272 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 5.257168 | 5.257168 | -0.680048 | -0.821762 | 0.973286 | 0.145441 | 0.925396 | 2.774753 | -0.971438 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | nn Power | 3.982738 | -0.856848 | -0.405035 | -0.488023 | 3.982738 | 0.937315 | -0.329987 | 1.696374 | 1.203954 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 5.505755 | 5.505755 | -1.049080 | -0.789439 | 1.407915 | 3.183383 | -0.825843 | 4.539166 | -1.207966 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 7.736295 | -0.271854 | 7.729247 | 0.825063 | -0.631210 | 0.555522 | 1.512398 | -0.995937 | 7.736295 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 4.823386 | -0.616560 | 3.606530 | 0.504790 | -0.618729 | -0.594447 | 3.976918 | -1.053786 | 4.823386 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 6.968338 | 5.653505 | -0.401279 | -0.421397 | 1.954498 | 1.284032 | 0.441090 | 6.968338 | 3.673110 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 5.332582 | -0.951539 | 3.869640 | 2.025250 | -0.332650 | -0.567175 | 4.323041 | -1.111612 | 5.332582 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 4.163518 | -0.694903 | 3.807696 | 1.066199 | -0.751555 | -0.923016 | 1.311611 | -0.246065 | 4.163518 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 3.986092 | 3.986092 | -0.055399 | -0.678177 | 1.496756 | 0.955029 | -0.152017 | 1.222230 | -0.837659 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | nn Power | 1.883983 | -0.657474 | 1.125065 | 1.883983 | -0.697792 | 1.756559 | -0.343370 | -1.509048 | 1.868401 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 6.634668 | 3.573627 | -0.841520 | -0.621610 | 1.482194 | 1.386167 | -0.341102 | 6.634668 | 4.188646 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 3.190428 | -0.620855 | 3.190428 | 1.597476 | -0.697152 | -0.410916 | 1.412981 | -0.004376 | 2.708131 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 5.900627 | 4.328342 | -0.456575 | -0.622889 | 1.455982 | 3.501769 | 1.003664 | 5.900627 | -0.718279 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 2.216198 | 2.216198 | -1.436970 | -0.461257 | 0.952967 | 0.364642 | 0.523069 | -0.094568 | -0.836959 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 3.548312 | -0.959766 | 3.548312 | 1.809948 | -0.845555 | 1.360679 | 0.976436 | -1.138694 | 0.905524 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Temporal Discontinuties | 3.891432 | -0.823916 | 2.455962 | 1.503651 | -0.847435 | 1.342223 | 1.016628 | -1.152500 | 3.891432 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 72 | N04 | digital_ok | ee Shape | 7.584946 | -0.744531 | 7.584946 | 1.114648 | -0.698578 | 0.316794 | 2.707307 | -0.262671 | 4.853688 |